A PRESENTATION TO THE SUMMER COLLOQUIUM ON CLIMATE AND HEALTH

1. REMOTELY SENSED INDICATORS OF MICRO-CLIMATE IN PREDICTING NEW AREAS OF HUMAN RISK OF LYME DISEASE USING SPATIAL STATISTICS AND ARTIFICIAL NEURAL NETWORKS A PRESENTATION TO THE SUMMER COLLOQUIUM ON CLIMATE AND HEALTH JULY 26, 2004, NCAR, BOULDER COLORADO RUSSELL BARBOUR PH.D. VECTOR ECOLOGY LABORATORY YALE SCHOOL OF MEDICINE NEW HAVEN CT.

2. PROBLEM STATEMENT • HUMAN CASE DATA HAS BEEN PROVEN AN UNRELIABLE INDICATOR OF LYME DISEASE RISK • UNDER REPORTING, MIS-DIAGNOSES, AND OVER REPORTING DISTORT HUMAN CASE DISTRIBUTION • COLLECTION AND TESTING OF INFECTED NYMPHS COSTLY

3. PROBLEMS CONTINUED • Ixodes scapularisTICKS HAVE NOT EXPANDED INTO ALL AREAS OF SUITABLE HABITAT • INVADING TICKS ARE NOT NECESSARILY INFECTED WITHBorrelia burgdorferei ( BACTERIAL AGENT OF LYME DISEASE) • ONLY INFECTED NYMPHAL TICKS POSE A THREAT TO HUMANS

4. NEW APPROACH TO RISK ESTIMATION AND PREDICTION • INTEGRATE HUMAN CASE DATA WITH LANDSCAPE INDICATORS OF THE NIDALITY (FOCI) OF INFECTION OF Borrelia burgdorferi • BUILD DATA LAYERS FROM REMOTELY SENSED MICRO-CLIMATE INDICATORS, PUBLISHED CANINE SEROPREVALENCE AND PREVIOUS HUMAN CASE DATA • DERIVE PROBABILITY OF INCREASING RISK THROUGH MARKOV-BAYES MONTE CARLO SIMULATIONS

5. KRIGING VERSUS MARKOV-BAYES MONTE CARLO CHAIN (MMCC) SIMULATION • KRIGING GIVES THE MOST LIKELY EVENT AT ALL LOCATIONS.. THE TOP OF A PROBABILITY DENSITY CURVE • KRIGING IS BASED ON JUST ONE “ ITERATION OF POSSIBLE REALITY” • KRIGING DISHONORS THE ORIGINAL DATA …“ EVENTS MORE PROBABLE THAN REALITY” • MMCC GIVES OTHER PROBABILITIES AT EACH LOCATION • MMCC HONORS THE ORIGINAL DATA • MMCC IS BASED ON METROPOLIS-HASTINGS RANDOM WALK (ALGORITHM USED TO DEVELOP H-BOMB). THE NEXT STATE IS ONLY DERIVED FROM THE CURRENT STATE • RANDOM WALK CREATES A NUMBER OF ITERATIONS ALTHOUGH EVENTUALLY THEY WILL CONVERGE TO KRIGED VALUES

7. EVI AS A FACTOR IN ESTIMATING LYME DISEASE RISK • MORE SENSITIVE TO PERIODS OF LIGHT VEGETATION , SPRING AND FALL WHEN NYMPHAL AND ADULT TICKS ARE ACTIVE • DISTINGUISHES BETWEEN WOODED SUBURBS AND TRUE FORESTS DURING THIS TIME PERIOD • IDENTIFIES DISCONTINUITY IN LANDSCAPES BETTER THAN NDVI

8. MODIS Products MODIS Ocean Atmosphere Land Products: MOD04 Aerosols MOD05 Water Vapor MOD06 Cloud MOD35 Cloud Mas … Products: MOD36 Ocean Color MOD28 SST … Products: MOD09 Reflectance MOD12 Snow Cover MOD13 Vegetation MOD14 Thermal Anomaly … SOURCE: http://modis.gsfc.nasa.gov/

9. Temporal Resolution Versions 250 m 500 m 1000 m 4 km 5 km 5 min 0.05 deg 0.25 deg Etc… daily 8-day composites 16-day composites 96-day composites Etc… Version3 v003 Version4 v004 MODIS Data products come in different Spatial Resolution ~But most products do NOT come with all these resolutions and versions~

12. RELATIONSHIP BY DATE BETWEEN HUMAN CASES AND EVI BY MOVING WINDOW ANALYSIS

13. MATHEMATICAL DATA INTEGRATION Most Abundant Data NEW REMOTELY SENSED VEGETATION INDEX (EVI) PREVIOUS HABITAT SUITABILITY MODEL CANINE SEROPREVALANCE DATA POINTS COMBINED BY ANN Sparse Data 1992- 2000 HUMAN CASE DATA BY COUNTY SPATIAL STATISTICS & MMCC SIMULATIONS ESTIMATED HUMAN CASES BY LOCATION

14. PREDICTIVE VALUE OF 1995 MID-WESTERN CASE DATA WHEN INTEGRATED WITH PREVIOUS YEARS AND LANDSCAPE INDICATORS OF INFECTION BY MULTILAYER ARTIFICIAL NEURAL NETWORKS PREDICTIVE VALUE YEAR

15. PREDICTIVE VALUE OF 1998 MID-WESTERN CASE DATA WHEN INTEGRATED WITH PREVIOUS YEARS AND LANDSCAPE INDICATORS OF INFECTION BY MULTILAYER ARTIFICIAL NEURAL NETWORKS

16. PROBABILITY OF HUMAN PREVALENCE HIGHER THAN 25/100,000 FROM 1992 HUMAN CASE DATA AND LANDSCAPE INFECTION INDICATORS URBAN AREAS PROBABILITY

17. PROBABILITY OF HUMAN PREVALENCE HIGHER THAN 25/100,000 FROM 2000 HUMAN CASE DATA AND LANDSCAPE INFECTION INDICATORS URBAN AREAS PROBABILITY

18. URBAN AREAS 1992 PROBABILITY OF HIGH PREVALENCE URBAN AREAS 2003 PROBABILITY OF HIGH PREVALENCE

19. PROBABILITY MAP

20. MODEL AGREEMENT WITH CASE DATA • PREDICTED SPATIAL HUMAN LD PREVALENCE BY FROM LANDSCAPE AND PREVIOUS HUMAN CASE DATA AGREED WITH ACTUAL CASES BY 81%

21. WEAKNESS • VEGETATION DATE TOO SPECIFIC • LARGE AREAS OF UNCERTAINTY • NO QUALITY CRITERIA FOR ORIGINAL CASE DATA • “NOISE” STILL PRESENT

22. STRENGTHS • HUMAN CASE DATA LINKED TO NIDALITY OF INFECTION • REASONABLE PREDICTIONS OF HUMAN RISK POSSIBLE • THREE YEAR ADVANCE OF INFECTION WALL APPEARS VISIBLE

23. WILDLIFE URBAN INTERFACE DATA LOW DENSITY INTERFACE : AREAS WITH HOUSING DENSITY BETWEEN 6.2 AND 49.4 HOUSING UNITS PER KM 2 AND 50% VEGETATION COVER WITHIN ALL 2 KM AREAS WITH 75 % COVER Source: SILVIS Lab Spatial Analysis For Conservation And SustainabilityForest Ecology & Management University Of Wisconsin - Madison

25. ASSOCIATED WITH HUMAN LD CASES In WI

26. SPATIAL STRUCTURE OF 2000 HUMAN CASE DATA IN WISCONSIN

27. CROSS VARIOGRAM2000 HUMAN CASES AND LOW DENSITY WUI

28. CO-KRIGE OF 2000 HUMAN CASES AND LOW WUI % LAND COVER

29. SPREAD OF INFECTED NYMPHAL Ixodes scapularis TICKS AS ESTIMATED FROM HUMAN CASES

30. FUTURE RESEARCH • CUBIC SPLINE REGRESSION OF ALL HUMAN CASE DATA TO REMOVE NOISE • ADDITION OF MODIS ATMOSPHERIC DATA TO CAPTURE HUMIDITY • FILTER OF UNSUITABLE LANDSCAPES FARMLAND • CALCULATION OF THE RATE OF INFECTION SPREAD, CURRENTLY ABOUT 6 KILOMETERS A YEAR, BASED ON MMCC PROBABILITY MODELS, NOT CASES